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Showing 1 - 20 results of 155 for search '(( data selection algorithm ) OR ( data duplication algorithm ))', query time: 0.11s Refine Results
  1. 1
    Variable Selection in Data Analysis: A Synthetic Data Toolkit

    Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

    Published 2024
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  2. 2
    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data

    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

    Published 2024
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  3. 3
    Bird’s Eye View feature selection for high-dimensional data

    Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

    Published 2023
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  4. 4
    An enhanced quorum selection algorithm

    An enhanced quorum selection algorithm by Haraty, Ramzi A.

    Published 2009
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  5. 5
    An Improved Quorum Selection Algorithm

    An Improved Quorum Selection Algorithm by Haraty, Ramzi A.

    Published 2008
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  6. 6
    A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks

    A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks by Umesh Kumar Lilhore (17727684)

    Published 2022
    “…The proposed model also utilized an enhanced back propagation neural network for data fusion operation, which is based on multi-hop system and also operates a highly optimized momentum technique, which helps to choose only optimum energy nodes and avoid duplicate selections that help to improve the overall energy and further reduce the quantity of data transmission. …”
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  7. 7
    An improved quorum selection algorithm (IQSA). (c2007)

    An improved quorum selection algorithm (IQSA). (c2007) by Younes, Samer

    Published 2007
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  8. 8
    Data mining approach to predict student's selection of program majors

    Data mining approach to predict student's selection of program majors by SIDDARTHA, SHARMILA

    Published 2019
    “…There is an opportunity to apply data mining to arrive at a model to predict student selection of a major. …”
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  9. 9
    A genetic algorithm for testable data path synthesis

    A genetic algorithm for testable data path synthesis by Harmanani, H.

    Published 2017
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  10. 10
    Nested ensemble selection: An effective hybrid feature selection method

    Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

    Published 2023
    “…The NES algorithm achieves perfect precision on the synthetic data and near optimal accuracy on the real-life data. …”
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  11. 11
    Application of Data Mining to Predict and Diagnose Diabetic Retinopathy

    Application of Data Mining to Predict and Diagnose Diabetic Retinopathy by Haniyeh, Maryam

    Published 2024
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  12. 12
    Multi-marker-LD based genetic algorithm for tag SNP selection

    Multi-marker-LD based genetic algorithm for tag SNP selection by Mansour, Nashat

    Published 2014
    “…The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. …”
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  13. 13
    Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms

    Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

    Published 2022
    “…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”
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  14. 14
    Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators

    Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

    Published 2021
    “…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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  15. 15
    Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection

    Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection by Atiq ur Rehman (3044409)

    Published 2024
    “…Although Evolutionary Algorithms (EAs) have shown promise in the literature for feature selection, creating EAs for high dimensions is still challenging. …”
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  16. 16
    Genetic and heuristic algorithms for regrouping service sites. (c2000)

    Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

    Published 2000
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  17. 17
    Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm

    Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm by Abu Zitar, Raed

    Published 2022
    “…Therefore, the smaller the difference between the selected pixels and the more correlation between two consecutive pixels, the less distortion can be achieved in the image after embedding the secret data. …”
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  18. 18
    Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011)

    Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011) by Abdallah, Raymond

    Published 2011
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  19. 19
    Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms

    Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms by Abdelouahed Hamdi (14158899)

    Published 2022
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  20. 20
    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks

    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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